Parameter estimation for INAR processes based on high-order statistics

• Tipo: Capítulo ou Parte de Livro
• Data: 2008

Autores

Isabel Silva (Autor) FEUP; M. Eduarda Silva (Autor) FEP

Livro

Título: COMPSTAT 2008 - Proceedings in Computational Statistics

Páginas: 965-972

ISBN: 9783790820836

ISBN Eletrónico: 9783790820843

Editora: Physica-Verlag HD

Classificação Científica

FOS: Ciências exactas e naturais > Matemática

CORDIS: Ciências Físicas > Matemática > Estatística

Outras Informações

Abstract (EN): The high-order statistics (moments and cumulants of order higher than two) have been widely applied in several fields, specially in problems where it is conjectured a lack of Gaussianity and/or non-linearity. Since the INteger-valued AutoRegressive, INAR, models are non-Gaussian, the high-order statistics can provide additional information that allows a better characterization of these processes. Thus, an estimation method for the parameters of an INAR model, based on Least Squares applied on third-order moments is proposed. The results of a Monte Carlo study, to investigate the performance of the estimator, are presented and the method is applied to a set of real data.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8